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@tpmjs/tools-permutation-test
Perform a permutation test to assess the statistical significance of the difference in means between two groups.
Installation
npm install @tpmjs/tools-permutation-test
Usage
import { permutationTestTool } from '@tpmjs/tools-permutation-test';
// Use with AI SDK
const result = await permutationTestTool.execute({
group1: [23, 25, 27, 29, 31],
group2: [18, 20, 22, 24, 26],
iterations: 10000, // optional, default: 10000
});
console.log(result);
// {
// pValue: 0.0234,
// observedDiff: 5,
// significant: true,
// iterations: 10000,
// metadata: {
// group1Size: 5,
// group2Size: 5,
// group1Mean: 27,
// group2Mean: 22,
// alpha: 0.05
// }
// }
Parameters
- group1 (number[], required): First group of numeric values
- group2 (number[], required): Second group of numeric values
- iterations (number, optional): Number of permutations to perform (default: 10000, min: 100, max: 100000)
Returns
{
pValue: number; // Two-tailed p-value
observedDiff: number; // Absolute difference in means
significant: boolean; // Whether p < 0.05
iterations: number; // Number of permutations performed
metadata: {
group1Size: number;
group2Size: number;
group1Mean: number;
group2Mean: number;
alpha: number; // Significance level (0.05)
}
}
How it works
The permutation test is a non-parametric method that doesn't assume normal distribution:
- Calculate the observed difference in means between the two groups
- Combine all values from both groups
- Randomly shuffle the combined data and split into two groups
- Calculate the difference in means for each permutation
- Count how many permutations have a difference as extreme or more extreme than observed
- Calculate p-value as the proportion of extreme permutations
When to use
- When you can't assume normal distribution
- With small sample sizes
- When comparing means between two independent groups
- Alternative to t-test when assumptions aren't met
License
MIT